The Overidentification of Autism in Asian American Student Populations

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Background: Students identified with disabilities have lower academic outcomes, decreased interaction with peers who do not have disabilities, and decreased postsecondary outcomes compared with peers who do not have disabilities. Educators must constantly work to ensure that identification of disability conditions is accurate and free from racial and cultural bias. Federal and state policies mandate that identification of a disability is not due to racial or cultural differences. Identifying racial or cultural differences as disability conditions has negative repercussions for both the student and the local education agency. In December of 2016, Title 34, Section 300.646, of the U.S. Code of Federal Regulations ordered states and local education agencies (LEAs) to collect and examine data in disability identification by race and ethnicity. This initiative was aimed at preventing racial discrimination in special education referrals. The regulations acknowledged that overidentification can lead to special education services for students when these services are not actually needed. This paper explored a trend which may have been unexpected but accounted for the largest category of overidentification of a specific disability condition by race/ethnicity in Texas in the year 2020. This category is the overidentification in Asian American students with autism, a disability condition which the Individuals with Disabilities Education Act defines as significantly affecting verbal communication, nonverbal communication, and social interaction. Purpose: The current study analyzed autism identification rates in 11 targeted Texas school districts. Each of the districts was cited by the Texas Education Agency in 2020 for overidentification of autism in Asian American student populations. This study also examined the autism evaluation procedures in two of these districts. These two districts eliminated significant disproportionality from 2020 to 2021. Methods: Two research questions involved quantitative analyses. Publicly available Results Driven Accountability reports from the Texas Education Agency were collected and analyzed for each of the 11 identified districts for the 2020 school year. These reports were analyzed in “SPED Representation (Ages 3-21)” to find specific data points related to special education, autism identification, and race/ethnicity. A third research question involved two of the 11 districts, which eliminated significant disproportionality from 2020 to 2021. Autism evaluation procedures for both districts were analyzed for references to adaptations to procedures for students who are culturally and linguistically diverse. Results: In 2020, the targeted districts identified autism in an average of 14.93% of special education students, compared to a state average of 13.70% and a national average of 11.10%. The districts identified autism in an average of 41.93% of Asian American students in special education, which was significantly higher than the average of 13.90% of non-Asian American students in special education. Two districts were successful in reducing significant disproportionality from 2020 to 2021 by employing evidence-based practices for evaluating culturally and linguistically diverse students. Conclusion: Overidentification of autism in Asian American students is a concerning trend which can be reversed with the use of evidence-based practices in the evaluation of culturally and linguistically diverse students. Included is an actionable plan which can be used by educators to implement these practices.

Autism, Asian American, Disproportionality, Cultural and Linguistic Diversity (CLD), Evidence Based Practices